PwC
Website:
pwc.com
Job details:
Job description - (preference would be given to Immediate to 40 days NP candidates.
Number of openings: 4 @ Kolkata / Bangalore / Mumbai
Years of experience required: 5+ years (with 1+ years in GenAI/LLM ecosystems)
Education qualification: B.E. / B.Tech / MCA/ M.E/ M.TECH/ MBA/ PGDM. All qualifications should be in regular full-time mode with no extension of course duration due to backlogs.
Interested candidates can directly share CV to amarjit.roy@pwc.com & mangala.hanamshetty.tpr@pwc.com with the subject line - GenAI | | | <your location Kolkata / Bangalore / Mumbai>
GenAI Application Development
· Develop GenAI applications using LLM APIs, prompt templates, structured outputs, RAG pipelines, embeddings, vector search, and tool calling.
· Build conversational AI, enterprise search, document Q&A, summarization, classification, data extraction, and workflow automation use cases.
· Integrate GenAI features with backend applications, portals, APIs, databases, document stores, and enterprise systems.
· Implement prompt orchestration, context management, response formatting, source citation handling, and feedback capture.
RAG, Semantic Search & Knowledge Ingestion
· Build document ingestion pipelines including parsing, OCR coordination, chunking, metadata extraction, embedding generation, indexing, and refresh.
· Implement semantic search and hybrid search using vector databases and search platforms.
· Support retrieval optimization through metadata filtering, chunking strategy, re-ranking, grounding, and citation generation.
· Work with enterprise knowledge sources such as SharePoint, Confluence, Google Drive, S3, databases, CRM, ITSM tools, and document repositories.
Agentic AI Development
· Develop basic to intermediate agentic workflows using LangChain, LangGraph, CrewAI, LlamaIndex, or equivalent frameworks.
· Implement agents with tools, memory, reasoning steps, API actions, and human-in-the-loop checkpoints.
· Build semi-autonomous workflows for business process automation while following safety and approval guardrails.
Backend, API & Data Engineering
· Develop backend services using Python, FastAPI, Node.js, or similar technologies.
· Build REST APIs for LLM orchestration, retrieval, ingestion, evaluation, semantic search, and agent execution.
· Work with SQL and NoSQL databases such as PostgreSQL, MySQL, SQL Server, MongoDB, Cosmos DB, DynamoDB, or equivalent.
· Use Redis or equivalent caching for session state, conversational memory, frequently accessed retrieval results, rate limiting, and workflow state.
· Follow secure coding, logging, exception handling, request validation, OpenAPI documentation, and production deployment practices.
Testing, Evaluation & Observability
· Support prompt testing, LLM response validation, RAG evaluation, regression testing, and hallucination checks.
· Use tools such as LangSmith, Langfuse, RAGAS, DeepEval, TruLens, Promptfoo, or equivalent under guidance.
· Capture logs, traces, token usage, latency, cost, feedback, and quality signals for GenAI applications.
Mandatory skill sets:
CORE GENAI - LLM APIs, prompt engineering, embeddings, RAG, semantic search, vector databases, structured outputs, grounding (Hands-on).
Frameworks - LangChain, LangGraph, CrewAI, LlamaIndex, Langflow (Hands-on).
Backend APIs - Python, FastAPI, Node.js, REST APIs, OpenAPI, async processing (Hands-on).
Data Stores - SQL, NoSQL, vector DB, Redis caching, object storage (Working knowledge).
Cloud AI - Azure OpenAI, AWS Bedrock, GCP Vertex AI, OpenAI, Anthropic Claude, Gemini, Hugging Face (Working knowledge).
Document Processing - PDF, Word, Excel, HTML, OCR, chunking, metadata extraction, indexing (Working knowledge).
Evaluation & Observability - LangSmith, Langfuse, RAGAS, Promptfoo, OpenTelemetry basics (Basic to working knowledge).
Security & Responsible AI - PII handling, access control, prompt injection awareness, content filtering, audit logging (Basic knowledge).
Soft Skills
· Strong problem-solving and analytical thinking.
· Ability to work in agile delivery teams and collaborate with cross-functional stakeholders.
· Good communication and documentation skills.
· Ability to learn and evaluate fast-evolving GenAI tools, frameworks, and patterns.
Preferred skill sets:
Exposure to Kafka or messaging systems for asynchronous processing.
· Exposure to MCP server development, tool integration patterns, or agent-to-tool communication.
· Basic understanding of A2A communication patterns and multi-agent orchestration.
· Familiarity with Docker, CI/CD, GitHub Actions, Azure DevOps, Jenkins, or equivalent.
· Exposure to fine-tuning, SLMs, vLLM, Ollama, or Hugging Face model deployment.
· Frontend integration awareness using React, Angular, Streamlit, Gradio, or similar.
· Domain exposure in banking, healthcare, insurance, retail, telecom, or enterprise operations.
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